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From action to activity: Sensor-based activity recognition
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DOI：10.1016/j.neucom.2015.08.096.png)
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摘要
En 中文
As compared to actions, activities are much more complex, but semantically they are more representative of a human's real life. Techniques for action recognition from sensor-generated data are mature. However, few efforts have targeted sensor-based activity recognition. In this paper, we present an efficient algorithm to identify temporal patterns among actions and utilize the identified patterns to represent activities for automated recognition. Experiments on a real-world dataset demonstrated that our approach is able to recognize activities with high accuracy from temporal patterns, and that temporal patterns can be used effectively as a mid-level feature for activity representation. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Activity recognition
Temporal pattern mining
Sensor-generated data
Discriminative feature extraction
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期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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